Big-O Notation

Big-O Notation

In this lesson — part of Complexity — you'll learn big-o notation in Kotlin and why it matters in real work.

Why it matters

Big-O tells you how code scales — the difference between instant and unusable on big data.

Key ideas

• Time and space complexity
• O(1), O(n), O(n log n), O(n²)
• Worst vs. average case
• Estimating from code

In practice

Here's the idea in pseudocode — the exact syntax varies by language:

// Kotlin: nested loops are O(n²)
for i in xs: for j in xs: ...

Try it yourself

Exercise: Classify the complexity of three small Kotlin snippets.

Recap

You now understand big-o notation and can apply it in Kotlin. Mark this lesson complete and continue to the next one.